DataFrame.groupby
Group DataFrame using a mapper or by a Series of columns.
danfo.DataFrame.groupby(columns)
Parameters | Type | Description | Default |
|---|---|---|---|
columns | Array | The names of a column(s) in the DataFrame to group by | |
Node
Browser
const dfd = require("danfojs-node")
let data = [["Pear", 2, 3], ["Pear", 5, 6], ["Apple", 30, 40], ["Apple", 89, 78]]
let cols = ["A", "B", "C"]
let df = new dfd.DataFrame(data, { columns: cols })
let group_df = df.groupby(["A"])
console.log(group_df)
// ouput
Groupby {
colDict: {
Pear: { A: [Array], B: [Array], C: [Array] },
Apple: { A: [Array], B: [Array], C: [Array] }
},
keyToValue: { Pear: [ 'Pear' ], Apple: [ 'Apple' ] },
keyCol: [ 'A' ],
data: [
[ 'Pear', 2, 3 ],
[ 'Pear', 5, 6 ],
[ 'Apple', 30, 40 ],
[ 'Apple', 89, 78 ]
],
columnName: [ 'A', 'B', 'C' ],
colDtype: [ 'string' ],
colIndex: [ 0 ]
}
A groupby operation will return a GroupBy class object. You can apply any of the following operation on the groupby result:
Node
const dfd = require("danfojs-node")
let data = [["Pear", 2, 3], ["Pear", 5, 6], ["Apple", 30, 40], ["Apple", 89, 78]]
let cols = ["A", "B", "C"]
let df = new dfd.DataFrame(data, { columns: cols })
let group_df = df.groupby(["A"]).sum()
group_df.print()
╔════════════╤═══════════════════╤═══════════════════╤═══════════════════╗
║ │ A │ B_sum │ C_sum ║
╟────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 0 │ Pear │ 7 │ 9 ║
╟────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 1 │ Apple │ 119 │ 118 ║
╚════════════╧═══════════════════╧═══════════════════╧═══════════════════╝
Node
Browser
const dfd = require("danfojs-node")
let data = [["Pear", 2, 3], ["Pear", 2, 6], ["Apple", 30, 40], ["Apple", 89, 78]]
let cols = ["A", "B", "C"]
let df = new dfd.DataFrame(data, { columns: cols })
let group_df = df.groupby(["A", "B"]).sum()
group_df.print()
╔════════════╤═══════════════════╤═══════════════════╤═══════════════════╗
║ │ A │ B │ C_sum ║
╟────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 0 │ Pear │ 2 │ 9 ║
╟────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 1 │ Apple │ 30 │ 40 ║
╟────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 2 │ Apple │ 89 │ 78 ║
╚════════════╧═══════════════════╧═══════════════════╧═══════════════════╝
Last modified 1yr ago